User Behavior Profile in a Blockchain

ABSTRACT

A method, system and computer-usable medium are disclosed for generating a cyber behavior profile, comprising: monitoring user interactions between a user and an information handling system; converting the user interactions and the information about the user into electronic information representing the user interactions; generating a unique cyber behavior profile based upon the electronic information representing the user interactions and the information about the user; and, storing information relating to the unique cyber behavior profile in a behavior blockchain.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates in general to the field of computers andsimilar technologies, and in particular to software utilized in thisfield. Still more particularly, it relates to a method, system andcomputer-usable medium for implementing a user behavior profile within ablockchain.

Description of the Related Art

Users interact with physical, system, data, content and servicesresources of all kinds, as well as each other, on a daily basis. Each ofthese interactions, whether accidental or intended, could pose somedegree of security risk to the owner of such resources depending on thebehavior of the user. In particular, the actions of a formerly trusteduser may become malicious as a result of being subverted, compromised orradicalized due to any number of internal or external factors orstressors. For example, financial pressure, political idealism,irrational thoughts, or other influences may adversely affect a user'sintent and/or behavior. Furthermore, such an insider threat may beintimately familiar with how systems operate, how they are protected,and how weaknesses can be exploited.

Both physical and cyber security efforts have traditionally beenoriented towards preventing or circumventing the intent of externalthreats. Physical security approaches have typically focused onmonitoring and restricting access to tangible resources. Likewise, cybersecurity approaches have included network access controls, intrusiondetection and prevention systems, machine learning, big data analysis,software patch management, and secured routers. Yet little progress hasbeen made in addressing the root cause of security breaches, primarilybecause the threat landscape is constantly shifting faster than currentthinking, which always seems to be one step behind technological change.

In particular, current data loss prevention (DLP) approaches primarilyfocus on enforcing policies for compliance, privacy, and the protectionof intellectual property (IP). Such approaches typically cover data atrest, in motion, and in use, across multiple channels including email,endpoints, networks, mobile devices, and cloud environments. However,the efficacy of such policies typically relies on enforcement of astatic set of rules governing what a user can and cannot do with certaindata. Various approaches for attempting to detect insider threats arealso known. For example, one approach to detecting such threats includesperforming user profiling operations to infer the intent of useractions. Another approach is to perform behavioral analysis operationswhen users are interacting with a system.

Nonetheless, many organizations first turn to technology to addressinsider threats, which include malicious cyber behavior by individualswho have legitimate rights to access and modify an organization'sresources, such as systems, data stores, services and facilities. Whilethe number of malicious users may be small (e.g., less than 0.1% of allusers in an organization), they may wreak serious financial and othertypes of damage. Accordingly, some organizations have implementedvarious machine learning approaches to identify anomalous or malicioususer behavior.

However, human behavior is often unpredictable and valid machinelearning training data may be difficult to obtain. Furthermore,identifying an impersonator that appears legitimate can proveproblematic, especially if their observed interactions with resourcesare limited. Likewise, it is often difficult to detect a trusted insiderbehaving in ways that appear normal but conceal nefarious motives. Humancomputers users are subject to the normality of life to include,vacations, job detail changes, interpersonal relationship stress andother daily occurrences making traditional behavioral baseline analysisdifficult without accounting for intermittent pattern features.Moreover, organizations typically have limited technical resources todevote to an insider threat program and are constrained in the types ofdata they can proactively collect and analyze.

SUMMARY OF THE INVENTION

A method, system and computer-usable medium are disclosed for generatinga cyber behavior profile, comprising: monitoring user interactionsbetween a user and an information handling system; converting the userinteractions and the information about the user into electronicinformation representing the user interactions; generating a uniquecyber behavior profile based upon the electronic informationrepresenting the user interactions and the information about the user;and, storing information relating to the unique cyber behavior profilein a behavior blockchain.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention may be better understood, and its numerousobjects, features and advantages made apparent to those skilled in theart by referencing the accompanying drawings. The use of the samereference number throughout the several figures designates a like orsimilar element.

FIG. 1 depicts an exemplary client computer in which the presentinvention may be implemented;

FIG. 2 is a simplified block diagram of electronically-observable userbehavior elements and their interrelationship;

FIG. 3 is a simplified block diagram of a user behavior monitoringsystem implemented to identify acceptable, anomalous, and malicious userbehavior;

FIG. 4 is a simplified block diagram of a user behavior profileimplemented as a blockchain;

FIG. 5 is a simplified block diagram of a user behavior block in ablockchain;

FIG. 6 is a simplified block diagram of a transportable user behaviorprofile;

FIGS. 7a and 7b are a generalized flowchart of the performance of userbehavior profile origination operations; and

FIGS. 8a and 8b are a generalized flowchart of the performance of userbehavior monitoring operations to detect acceptable, anomalous, andmalicious cyber behavior.

DETAILED DESCRIPTION

A method, system and computer-usable medium are disclosed for detectingacceptable, anomalous, and malicious user behavior. For purposes of thisdisclosure, an information handling system may include anyinstrumentality or aggregate of instrumentalities operable to compute,classify, process, transmit, receive, retrieve, originate, switch,store, display, manifest, detect, record, reproduce, handle, or utilizeany form of information, intelligence, or data for business, scientific,control, or other purposes. For example, an information handling systemmay be a personal computer, a mobile device such as a tablet orsmartphone, a connected “smart device,” a network appliance, a networkstorage device, or any other suitable device and may vary in size,shape, performance, functionality, and price. The information handlingsystem may include random access memory (RAM), one or more processingresources such as a central processing unit (CPU) or hardware orsoftware control logic, ROM, and/or other types of nonvolatile memory.Additional components of the information handling system may include oneor more storage systems, one or more network ports for communicatingexternally, as well as various input and output (I/O) devices, such as akeyboard, a mouse, and a graphics display.

FIG. 1 is a generalized illustration of an information handling system100 that can be used to implement the system and method of the presentinvention. The information handling system 100 includes a processor(e.g., central processor unit or “CPU”) 102, input/output (I/O) devices104, such as a display, a keyboard, a mouse, and associated controllers,a storage system 106, and various other subsystems 108. In variousembodiments, the information handling system 100 also includes networkport 110 operable to connect to a network 140, which is likewiseaccessible by a service provider server 142. The information handlingsystem 100 likewise includes system memory 112, which is interconnectedto the foregoing via one or more buses 114. System memory 112 furtherincludes operating system (OS) 116 and in various embodiments may alsoinclude a user behavior monitoring system 118. In one embodiment, theinformation handling system 100 is able to download the user behaviormonitoring system 118 from the service provider server 142. In anotherembodiment, the user behavior monitoring system 118 is provided as aservice from the service provider server 142.

In various embodiments, the user behavior monitoring system 118 performsa detection operation to determine whether a particular behaviorassociated with a given user is acceptable, unacceptable, anomalous, ormalicious. In certain embodiments, a behavior may include variousprocesses performed at the behest of a user, such as a physical or cyberbehavior, described in greater detail herein. In various embodiments,the detection operation is performed to attribute such processes to theuser associated with the acceptable, unacceptable, anomalous, ormalicious behavior. In certain embodiments, the detection operationimproves processor efficiency, and thus the efficiency of theinformation handling system 100, by automatically identifyingacceptable, unacceptable, anomalous, or malicious behavior.

As will be appreciated, once the information handling system 100 isconfigured to perform the acceptable, unacceptable, anomalous, ormalicious behavior detection operation, the information handling system100 becomes a specialized computing device specifically configured toperform the acceptable, anomalous, or malicious behavior detectionoperation (i.e., a specialized user-centric information handling system)and is not a general purpose computing device. Moreover, theimplementation of the user behavior detection monitoring system 118 onthe information handling system 100 improves the functionality of theinformation handling system 100 and provides a useful and concreteresult of automatically detecting acceptable, anomalous, and maliciousbehavior associated with a user.

FIG. 2 is a simplified block diagram of electronically-observable userbehavior elements implemented in accordance with an embodiment of theinvention and their interrelationship. As used herein,electronically-observable user behavior broadly refers to any behaviorexhibited or enacted by a user that can be electronically observed. Invarious embodiments, user behavior may include a user's physicalbehavior, cyber behavior, or a combination thereof. As likewise usedherein, physical behavior broadly refers to any user behavior occurringwithin a physical realm such as speaking, voice, facial patterns,walking. More particularly, physical behavior may include any activityenacted by a user that can be objectively observed, or indirectlyinferred, within a physical realm.

A physical behavior element, as likewise used herein, broadly refers toa user's behavior in the performance of a particular action within aphysical realm. As an example, a user, such as user ‘A’ 202 or ‘B’ 262,may attempt to use an electronic access card to enter a securedbuilding. In this example, the use of the access card to enter thebuilding is the action and the reading of the access card makes theuser's physical behavior electronically-observable. As another example,user ‘A’ 202 may physically deliver a document to user ‘B’ 262, which iscaptured by a video surveillance system. In this example, the physicaldelivery of the document to the other user ‘B’ 262 is the action and thevideo record of the delivery makes the user's physical behaviorelectronically-observable.

Cyber behavior, as used herein, broadly refers to any user behavioroccurring within cyberspace. More particularly, cyber behavior mayinclude physical, social, or mental activities enacted by a user thatcan be objectively observed, directly or indirectly, or indirectlyinferred, within or via cyberspace. As likewise used herein, cyberspacebroadly refers to a network environment, such as an internal 244 orexternal 246 network, capable of supporting communication of informationbetween two or more entities. In various embodiments, the entity may bea user, such as user ‘A’ 202 or ‘B’ 262, a user device 230, or variousresources 250. In certain embodiments, the entities may include varioususer devices 230 or resources 250 operating at the behest of a user,such as user ‘A’ 202 or ‘B’ 262. In various embodiments, thecommunication between the entities may include audio, image, video,text, or binary data.

In various embodiments, the communication of the information may takeplace in real-time or near-real-time. As an example, a cellular phoneconversation may be used to communicate information in real-time, whilean instant message (IM) exchange may be used to communicate informationin near-real-time. In certain embodiments, the communication of theinformation may take place asynchronously. For example, an email messagemay be stored on a user device 230 when it is offline. In this example,the information may be communicated to its intended recipient once theuser device 230 gains access to an internal 244 or external 246 network.

A cyber behavior element, as likewise used herein, broadly refers to auser's behavior during the performance of a particular action withincyberspace. As an example, user ‘A’ 202 may use a user device 230 tobrowse a particular web page on a news site on the Internet. In thisexample, the individual actions performed by user ‘A’ 202 to access theweb page constitute a cyber behavior element. As another example, user‘A’ 202 may use a user device 230 to download a data file from aparticular system 254. In this example, the individual actions performedby user ‘A’ 202 to download the data file, including the use of one ormore user authentication factors 204 for user authentication, constitutea cyber behavior element. In these examples, the actions are enactedwithin cyberspace, which makes them electronically-observable.

In various embodiments, a physical or cyber behavior element may includeone or more user behavior activities. A physical or cyber behavioractivity, as used herein, broadly refers to one or more discrete actionsperformed by a user, such as user ‘A’ 202 or ‘B’ 262, to enact acorresponding physical or cyber behavior element. In variousembodiments, such physical or cyber behavior activities may include theuse of user authentication factors 204, user behavior factors 212, or acombination thereof, in the enactment of a user's physical or cyberbehavior. In certain embodiments, the user authentication factors 204are used in authentication approaches familiar to skilled practitionersof the art to authenticate a user, such as user ‘A’ 202 or ‘B’ 262. Invarious embodiments, the user authentication factors 204 may includebiometrics 206 (e.g., a finger print, a retinal scan, etc.), securitytokens 208 (e.g., a dongle containing cryptographic keys), or a useridentifier/password (ID/PW) 210.

In certain embodiments, the user behavior factors 212 may include theuser's role 214 (e.g., title, position, role, etc.), the user's accessrights 216, the user's interactions 218, and the date/time/frequency 220of those interactions 218. In various embodiments, the user behaviorfactors 212 may likewise include the user's location 222 when theinteractions 218 are enacted, and user gestures 224 used to enact theinteractions 218. In certain embodiments, the user gestures 224 mayinclude key strokes on a keypad, a cursor movement, a mouse movement orclick, a finger swipe, tap, or other hand gesture, an eye movement, orsome combination thereof. In various embodiments, the user gestures 224may likewise the cadence of the user's keystrokes, the motion, force andduration of a hand or finger gesture, the rapidity and direction ofvarious eye movements, or some combination thereof. In one embodiment,the user gestures 224 may include various audio or verbal commandsperformed by the user. In various embodiments, the user behavior factors212 may include associated additional context regarding the capturedbehavior of the user. For example, additional context might indicate theuser was on vacation, the user is in new job role, the user is beingterminated in 30 days, etc. Additionally, the additional context couldbe more complex to include changes in user communication relationshipsor semantics of created content and communications. In certainembodiments, the additional context might include tags to verboselycontextualize a smaller design element. In certain embodiments, the tagscan be generated from meta analytic sources. In certain embodiments, theadditional context could be tagged post—event and then associated withthe user behavior factors. In certain embodiments, the association mightbe via a blockchain block within a user behavior profile blockchain withappropriate time stamping to allow for versioning over time.

In certain embodiments, the user interactions 218 may includeuser/device 228, user/network 242, user/resource 248, user/user 260interactions, or some combination thereof. In various embodiments, theuser/device 228 interactions include an interaction between a user, suchas user ‘A’ 202 or ‘B’ 262 and a user device 230. As used herein, a userdevice 230 refers to an information processing system such as a personalcomputer, a laptop computer, a tablet computer, a personal digitalassistant (PDA), a smart phone, a mobile telephone, or other device thatis capable of processing and communicating data. In certain embodiments,the user device 230 is used to communicate data through the use of aninternal network 244, an external network 246, or a combination thereof.

In various embodiments, the cyber behavior element may be based upon amachine readable representation of some or all of one or more useridentification factors 226. In various embodiments, the useridentification factors 226 may include biometric information,personality type information, technical skill level, financialinformation location information, peer information, social networkinformation, or a combination thereof. The user identification factors226 may likewise include expense account information, paid time off(PTO) information, data analysis information, personally sensitiveinformation (PSI), personally identifiable information (PII), or acombination thereof. Likewise, the user identification factors 226 mayinclude insider information, misconfiguration information, third partyinformation, or a combination thereof. Skilled practitioners of the artwill recognize that many such embodiments are possible. Accordingly, theforegoing is not intended to limit the spirit, scope or intent of theinvention.

In certain embodiments, the user device 230 is configured to receivelocation data 236, which is used as a data source for determining theuser's location 222. In one embodiment, the location data 236 mayinclude Geographical Positioning System (GPS) data provided by a GPSsatellite 238. In another embodiment the location data 236 may includelocation data 236 provided by a wireless network, such as from acellular network tower 240. In yet another embodiment (not shown), thelocation data 236 may include various Internet Protocol (IP) addressinformation assigned to the user device 230. In yet still anotherembodiment (also not shown), the location data 236 may includerecognizable structures or physical addresses within a digital image orvideo recording.

In various embodiments, the user devices 230 may also include an inputdevice (not shown), such as a keypad, magnetic card reader, tokeninterface, biometric sensor, digital camera, video surveillance camera,and so forth. In these embodiments, such user devices 230 may bedirectly, or indirectly, connected to a particular facility 252 orsystem 254. As an example, the user device 230 may be directly connectedto an ingress/egress system, such as an electronic lock on a door or anaccess gate of a parking garage. As another example, the user device 230may be indirectly connected to a physical security mechanism through adedicated security network.

In certain embodiments, the user/device 228 interaction may includeinteraction with a user device 230 that is not connected to a network atthe time the interaction occurs. As an example, user ‘A’ 202 or ‘B’ 262may interact with a user device 230 that is offline, using applications232, accessing data 234, or a combination thereof, it contains. Thoseuser/device 228 interactions, or their result, may be stored on the userdevice 230 and then be accessed or retrieved at a later time once theuser device 230 establishes a connection to the internal 244 or external246 networks.

In various embodiments, the user/network 242 interactions may includeinteractions with an internal 244 network, an external 246 network, orsome combination thereof. In these embodiments, the internal 244 and theexternal 246 networks may include a public network, such as theInternet, a physical private network, a virtual private network (VPN),TOR network, or any combination thereof. In certain embodiments, theinternal 244 and external 246 networks may likewise include a wirelessnetwork, including a personal area network (PAN), based on technologiessuch as Bluetooth. In various embodiments, the wireless network mayinclude a wireless local area network (WLAN), based on variations of theIEEE 802.11 specification, commonly referred to as WiFi. In certainembodiments, the wireless network may include a wireless wide areanetwork (WWAN) based on an industry standard including various 3G, 4Gand 5G technologies.

In various embodiments the user/resource 248 interactions may includeinteractions with various resources 250. In certain embodiments, theresources 250 may include various facilities 252 and systems 254, eitherof which may be physical or virtual, as well as data stores 256 andservices 258. In various embodiments, the user/user 260 interactions mayinclude interactions between two or more users, such as user ‘A’ 202 and‘B’ 262. In these embodiments, the user/user interactions 260 may bephysical, such as a face-to-face meeting, via a user/device 228interaction, a user/network 242 interaction, a user/resource 248interaction, or some combination thereof.

In one embodiment, the user/user 260 interaction may include aface-to-face verbal exchange between two users. In another embodiment,the user/user 260 interaction may include a written exchange, such astext written on a sheet of paper, between two users. In yet anotherembodiment, the user/user 260 interaction may include a face-to-faceexchange of gestures, such as a sign language exchange, between twousers. Those of skill in the art will recognize that many such examplesof user/device 228, user/network 242, user/resource 248, and user/user260 interactions are possible. Accordingly, the foregoing is notintended to limit the spirit, scope or intent of the invention.

In certain embodiments, the user authentication factors 204 are used incombination to perform multi-factor authentication of a user, such asuser ‘A’ 202 or ‘B’ 262. As used herein, multi-factor authenticationbroadly refers to approaches requiring two or more authenticationfactors. In general, multi-factor authentication includes three classesof user authentication factors 204. The first is something the userknows, such as a user ID/PW 210. The second is something the userpossesses, such as a security token 208. The third is something that isinherent to the user, such as a biometric 206.

In various embodiments, multi-factor authentication is extended toinclude a fourth class of factors, which includes one or more userbehavior factors 212, one or more user identification factors 226, or acombination thereof. In these embodiments, the fourth class of factorsincludes user behavior elements the user has done, is currently doing,or is expected to do in the future. In certain embodiments, multi-factorauthentication is performed on recurring basis. In one embodiment, themulti-factor authentication is performed at certain time intervalsduring the enactment of a particular user behavior. In anotherembodiment, the time interval is uniform. In yet another embodiment, thetime interval may vary or be random. In yet still another embodiment,the multi-factor authentication is performed according to the enactmentof a particular user behavior, such as accessing a different resource250.

In various embodiments, certain combinations of the enhancedmulti-factor authentication described herein are used according to theenactment of a particular user behavior. From the foregoing, those ofskill in the art will recognize that the addition of such a fourth classof factors not only strengthens current multi-factor authenticationapproaches, but further, allows the factors to be more uniquelyassociated with a given user. Skilled practitioners of the art willlikewise realize that many such embodiments are possible. Accordingly,the foregoing is not intended to limit the spirit, scope or intent ofthe invention.

FIG. 3 is a simplified block diagram of a user behavior monitoringsystem implemented in accordance with an embodiment of the invention todetect acceptable, anomalous, and malicious user behavior. In variousembodiments, user behavior profiles ‘1’ 372 through ‘n’ 374 arerespectively generated, as described in greater detail herein, for users‘1’ 302 through ‘n’ 304. As used herein, a user behavior profile broadlyrefers to various enactments of user behavior associated with aparticular user, such as users ‘1’ 302 through ‘n’ 304. In variousembodiments, a user behavior profile is based upon one or moreidentification factors and/or one or more user behavior factors (i.e., auser behavior profile may include and/or may be derived from one or moreidentification factors and/or user behavior factors). In variousembodiments, a function or model may be applied to one or moreidentification factors and/or user behavior factors to generate a userbehavior profile. In various embodiments, one or more identificationfactors and/or user behavior factors may be enriched when generating auser behavior profile. It will be appreciated that the user behavior ofa particular user, over time, will be uniquely different. Accordingly,user behavior profile ‘1’ 372 will uniquely reflect the user behavior ofuser ‘1’ 302, just as user behavior profile ‘n’ 374 will uniquelyreflect the user behavior of user ‘n’ 310.

In various embodiments, a user behavior monitoring system 118 isimplemented to observe user behavior 306 at one or more points ofobservation within a cyberspace environment. In certain embodiments, thepoints of observation may occur during various user interactions, suchas user/device 228, user/network 242, user/resource 248, and user/user260 interactions described in greater detail herein. As an example, auser/user 260 interaction may include an interaction between anindividual user ‘1’ 302 through ‘n’ 304 with user ‘x’ 314. In variousembodiments, the point of observation may include cyber behavior ofvarious kinds within an internal 244 network. As an example, cyberbehavior within an internal 244 network may include a user accessing aparticular internal system 254 or data store 256. In certainembodiments, the point of observation may include cyber behavior ofvarious kinds within an external 246 network. As an example, cyberbehavior within an external 246 network may include a user's socialmedia activities or participation in certain user forums.

In various embodiments, the user behavior profile ‘1’ 372 through ‘n’374 associated with a given user, such as user ‘1’ 302 through ‘n’ 304,is used by the user behavior monitoring system 118 to compare the user'scurrent user behavior 306 to past user behavior 306. If the user'scurrent user behavior 306 matches past user behavior 306, then the userbehavior monitoring system 118 may determine that the user's userbehavior 306 is acceptable 308. However, if not, then the user behaviormonitoring system 118 may determine that the user's user behavior 306 isanomalous 310 or malicious 312.

In these embodiments, it will be appreciated that anomalous 310 userbehavior 306 may include inadvertent or compromised user behavior 306.For example, the user may have innocently miss-entered a request fordata that is proprietary to an organization. As another example, theuser may be attempting to access confidential information as a result ofbeing compromised. As yet another example, a user may attempt to accesscertain proprietary data from their home, over a weekend, late at night.In this example, the user may be working from home on a project with animpending deadline. Accordingly, the attempt to access the proprietarydata is legitimate, yet still anomalous as the attempt did not occurduring the week from the user's place of employment. Further, thebehavior, however, may manifest in context with consistent remote accesspatterns and provide sufficient evidence to determine the nature ofactivity.

Likewise, the user behavior monitoring system 118 may determine that theuser's user behavior 306 to be malicious 312. As yet another example, animpostor may be attempting to pose as a legitimate user in an attempt toexploit one or more resources 250. In this example, the attempt toexploit one or more resources 250 is malicious 312 user behavior 306. Asyet still another example, a legitimate user may be attempting toincrease their level of access to one or more resources 250. In thisexample, the user's attempt to increase their level of access ismalicious 312 user behavior 306.

To further extend these examples, such resources may include variousfacilities 252, systems 254, data stores 256, or services 258. Invarious embodiments, the user behavior monitoring system 118 may beimplemented to block a user if it is determined their user behavior 306is anomalous 310 or malicious 312. In certain embodiments, the userbehavior monitoring system 118 may be implemented modify a requestsubmitted by a user if it is determined the request is anomalous 310 ormalicious 312.

In one embodiment, the user behavior monitoring system 118 may beimplemented as a stand-alone system. In another embodiment, the cyberbehavior monitoring system 118 may be implemented as a distributedsystem. In yet another embodiment, the cyber behavior monitoring system118 may be implemented as a virtual system, such as an instantiation ofone or more virtual machines (VMs). In yet still another embodiment, theuser behavior monitoring system 118 may be implemented as a userbehavior monitoring service 366. Skilled practitioners of the art willrecognize that many such embodiments and examples are possible.Accordingly, the foregoing is not intended to limit the spirit, scope orintent of the invention.

In various embodiments, user behavior detection operations are initiatedby first authenticating a user, such as user ‘1’ 302 through ‘n’ 304.Once authenticated, the user's respective user behavior profile isretrieved, followed by ongoing monitoring of the user's user behavioractivities. The user's user behavior activities are then processed todetermine an associated user behavior element, which in turn is comparedto the user's user behavior profile. In various embodiments, the userbehavior profile is continually amended and refined based on thecontinuous interaction with the system over time.

A determination is then made whether the user's current user behaviorelement, or group of behavior elements, is acceptable. In certainembodiments, the determination combines the current user behaviorelement with other user behavior elements such that the group ofbehavior elements corresponds to a group of events which may be analyzedto determine whether behavior elements of the group of behavior elementsare acceptable. If so, then the user's current user behavior element ismarked as acceptable. Otherwise, a determination is made whether theuser's current user behavior element is anomalous. If so, then theuser's current user behavior element is marked as anomalous, followed bythe performance of anomalous user behavior operations. In variousembodiments, the anomalous user behavior operations can include ananomalous user behavior notification operation and/or an anomalous userresponse operation. In various embodiments, the anomalous user responseoperation can include a user blocking operation where an action is takento restrict or remove user access to some or all of the user devices 230and/or resources 250 and/or a risk level adjustment operation where arisk score associated with the user is adjusted based upon the anomalousbehavior. In one embodiment, the anomalous user behavior element isstored for later review. In another embodiment, a security administrator368 is notified of the anomalous user behavior element.

However, if it was determined that the user's current user behaviorelement was not anomalous, then it is marked as malicious (orunacceptable), followed by the performance of malicious behavioroperations. In various embodiments, the malicious user behavioroperations can include a malicious user behavior notification operationand/or a malicious user behavior response operation. In variousembodiments, the malicious user response operation can include a userblocking operation where an action is taken to restrict or remove useraccess to some or all of the user devices 230 and/or resources 250and/or a risk level adjustment operation where a risk score associatedwith the user is adjusted based upon the anomalous behavior. In oneembodiment, the malicious user behavior element is stored for laterreview. In another embodiment, a security administrator 368 is notifiedof the malicious user behavior element. Thereafter, the current userbehavior element, whether marked acceptable, anomalous, malicious orunknown, is appended, as described in greater detail herein, to theuser's user behavior profile. Once the user's user behavior activitieshave concluded, user behavior profile scoring and hashing operations,likewise described in greater detail herein, are performed torespectively generate a user behavior profile score and hash. Theresulting user behavior profile score and hash are then appended to theuser's user behavior profile.

In various embodiments, user behavior profiles are stored in arepository of user behavior profiles 370. In one embodiment, therepository of user behavior profiles 370 is implemented for use by asingle user behavior monitoring system 118. In another embodiment, therepository of user behavior profiles 370 is implemented for use by aplurality of user behavior monitoring systems 118. In yet anotherembodiment, the repository of user behavior profiles 370 is implementedfor use by a user behavior monitoring service 366. Skilled practitionersof the art will recognize that many such embodiments are possible.Accordingly, the foregoing is not intended to limit the spirit, scope orintent of the invention.

FIG. 4 is a simplified block diagram of a user behavior profileimplemented in accordance with an embodiment of the invention as ablockchain. As used herein, a blockchain broadly refers to a datastructure that is tamper evident and appendable. In certain embodiments,a block chain further refers to a decentralized, distributed datastructure whose contents are replicated across a number of systems.These contents are stored in a chain of fixed structures commonlyreferred to as “blocks,” such as user behavior block ‘1’ 410, block ‘2’412, and so forth, through block ‘n’ 414. Each of these blocks containscertain information about itself, such as a unique identifier, areference to its previous block, and a hash value generated from thedata it contains. As an example, user behavior block ‘2’ 412 wouldcontain a reference to user behavior block ‘1 410, yet their respectivehashes values would be different as they contain different data.

Those of skill in the art will be aware that blockchains may beimplemented in different ways and for different purposes. However, thesedifferent implementations typically have certain common characteristics.For example in certain embodiments, blockchains are generallydistributed across various systems, each of which maintains a copy ofthe blockchain. Updates to one copy of the blockchain, such as theaddition of a user behavior block ‘n’ 414, results in correspondingupdates to the other copies. Accordingly, the contents of theblockchain, including its most recent updates, are available to allparticipating users of the blockchain, who in turn use their own systemsto authenticate and verify each new block. This process ofauthentication and verification ensures that the same transaction doesnot occur more than once. Furthermore with distributed types of blockchains, the legitimacy of a given block, and its associated contents, isonly certified once a majority of participants agree to its validity.

In general, the distributed and replicated nature of a blockchain, suchas a user behavior blockchain 408, makes it difficult to modifyhistorical records without invalidating any subsequent blocks addedthereafter. As a result, the user behavior data within a given userbehavior blockchain 408 is essentially immutable and tamper-evident.However, this immutability and tamper-evidence does not necessarilyensure that the user behavior data recorded in the cyber behaviorblockchain 408 can be accepted as an incontrovertible truth. Instead, itsimply means that what was originally recorded was agreed upon by amajority of the user behavior blockchain's 408 participants.

Additionally certain embodiments include an appreciation that everytransaction in a blockchain is serialized (i.e., stored in a sequence).Additionally in certain embodiments, every transaction in a block chainis time-stamped, which is useful for tracking interactions betweenparticipants and verifying various information contained in, or relatedto, a blockchain. Furthermore, instructions can be embedded withinindividual blocks of a blockchain. These instructions, in the form ofcomputer-executable code, allow transactions or other operations to beinitiated if certain conditions are met.

Referring now to FIG. 4, groups of user behavior activities 402,described in greater detail herein, are combined in various embodimentsto generate one or more associated user behavior elements 404, likewisedescribed in greater detail herein. In certain embodiments, the userbehavior element is used to generate a user behavior block 414. Incertain embodiments, the resulting user behavior elements 404 are inturn combined to generate a user behavior block, such as user behaviorblock ‘n’ 414. The resulting user behavior block is then appended to atarget user behavior blockchain, such as user behavior blockchain 408.As used herein, a user behavior block broadly refers to a blockchainblock implemented to contain various user behavior data. As likewiseused herein, user behavior data broadly refers to any data associatedwith a user's user behavior, as described in greater detail herein.

In various embodiments, a user behavior blockchain 408 is implemented tocontain one or more user behavior profiles 406, described in greaterdetail herein. In one embodiment, the user behavior blockchain 408contains a single user behavior profile 406, which in turn is associatedwith an individual user. In this embodiment, user behavior blocks ‘1’410 and ‘2’ 412 through ‘n’ 414 are associated with the individual user.In another embodiment, the user behavior blockchain 408 is implementedto include user behavior profiles 406 associated with two or more users.In this embodiment, individual user behavior blocks ‘1’ 410 and ‘2’ 412through ‘n’ 414 are respectively associated with two or more userbehavior profiles 406, which in turn are respectively associated with aparticular user. In certain embodiments, the user behavior blockchain408 is parsed to identify which of the user behavior blocks ‘1’ 410 and‘2’ 412 through ‘n’ 414 are associated with a given user behaviorprofile 406, which in turn are respectively associated with a particularuser.

In various embodiments, data associated with a given user behaviorblockchain 408 is used in the performance of user behavior monitoringoperations to detect acceptable, anomalous, malicious and unknownbehavior enacted by a user. In certain embodiments, the performance ofthese user behavior monitoring operations involve comparing anewly-generated user behavior block, such as user behavior block ‘n’ 414to previously-generated user behavior blocks, such as user behaviorblocks ‘1’ 410 and ‘2’ 412.

In certain embodiments, if the contents of the user behavior block ‘n’414 are substantively similar to the contents of user behavior blocks‘1’ 410 and ‘2’ 412, then the behavior of the user may be judged to beacceptable. However, if the contents of the user behavior block ‘n’ 414are substantively dissimilar to the contents of user behavior blocks ‘1’410 and ‘2’ 412, then the behavior of the user may be judged to beanomalous, malicious or unknown. In these embodiments, the method bywhich the contents of user behavior block ‘n’ 414 are determined to besubstantively similar, or dissimilar, to the contents of user behaviorblocks ‘1’ 410 and ‘2’ 412 is a matter of design choice.

FIG. 5 is a simplified block diagram of a user behavior block in ablockchain implemented in accordance with an embodiment of theinvention. In various embodiments, a blockchain user behavior blockchain408, as shown in FIG. 4, may contain one or more user behavior blocks502, such as user behavior block ‘1’ 410, and ‘2’ 412 through ‘n’ 414,likewise shown in FIG. 4. In these embodiments, each user behavior block502 may include either or both data and metadata, such as a blockreference identifier (ID) 504, a hash value of the prior user behaviorblock's header 506 information, the public key of the recipient 508 ofthe user behavior blockchain 408 transaction, and the digital signatureof the originator 510 of the user behavior blockchain 408 transaction.The user behavior block 502 may likewise include additional either orboth data and metadata, such as a user behavior blockchain transactionidentifier 512, a transaction payload 514, and a transaction timestamp516.

In certain embodiments, the transaction payload 514 may include one ormore user behavior profiles 518. In various embodiments, a user behaviorprofile 518 may include various user behavior elements 524, described ingreater detail herein, and a hash 520 value of the user behaviorelements 524. In certain embodiments, the hash 520 value is implementedto determine whether the integrity of the user behavior elements 524 hasbeen compromised. In various embodiments, the user behavior profile 518may include executable code 526. In certain embodiments, the executablecode 526 may be used by a user behavior monitoring system, described ingreater detail herein, to detect acceptable, anomalous, malicious andunknown behavior being enacted by a user. In various embodiments, userbehavior data contained in one or more user behavior elements 524 isused in combination with the executable code to perform user behaviormonitoring operations, likewise described in greater detail herein. Incertain embodiments, the executable code can include state informationsuch as pre-calculated information associated with one or more userbehavior elements 524. In certain embodiments, the executable code 526can include a model of good behavior which is used when detectingacceptable, anomalous, malicious and unknown behavior being enacted by auser. In certain embodiments, the model includes a series of rules ofbehaviors that might lead to a determination regarding trustworthiness.In certain embodiments, the series of rules can include communicationrelated rules, data movement related rules and/or programmingmodification type rules. Such a model enables the system to access anintent of a user.

In certain embodiments, the user behavior block 502 may also contain arisk score 522. In certain embodiments, the risk score includes a userbehavior score. In various embodiments, the risk score 522 may be usedby a user behavior monitoring system to assess the state (e.g., the riskor trustworthiness) of a particular user while enacting a given userbehavior. In certain embodiments, the state may also be stored withinthe user behavior block 502. In certain embodiments, the state isassessed at a specific time and has a time associated with the state. Inone embodiment, the user behavior score 522 might be associated with aparticular user behavior element, such as accessing sensitive humanresource documents. In one embodiment, the user behavior score 522 mightbe related to a user's overall user behavior. In various embodiments,the user behavior block 502 may also contain information regarding howthe user behavior score was generated such as the model that was used togenerate the user behavior score. Storing this information provides ahistorical view of how the score was generated when the score wasgenerated. Certain embodiments include an appreciation that thisinformation can be useful in identifying what type of user behavior ledto the user behavior score (e.g., what was the anomaly).

As an example, a user may have a high user behavior score 522 forgeneral cyberspace activity, but a low user behavior score 522 foraccessing an organization's financial data. To continue the example, theuser's role in the organization may be related to maintaining a physicalfacility. In that role, the user may requisition cleaning supplies andschedule other users to perform maintenance. Accordingly, attempting toaccess the organization's financial data, particularly over a weekend,would indicate anomalous, or possibly malicious, behavior. To continuethe example, such an attempt may result in a low user behavior score 522being assigned to that particular user behavior element. Those of skillin the art will recognize that many such embodiments and examples arepossible. Accordingly, the foregoing is not intended to limit thespirit, scope or intent of the invention. In certain embodiments, theuser behavior score 522 may change as a result of information obtainedfrom a third party and not just from observable behavior. For example,in another type of score if a credit score of a user changes, or theuser performs a wire transfer to a known suspicious location, then theuser behavior score 522 may be changed based upon this information.

FIG. 6 is a simplified block diagram of a transportable user behaviorprofile implemented in accordance with an embodiment of the invention.In this embodiment, a user behavior profile 406 for a user 602 may beimplemented as a user behavior blockchain 408, as shown in FIG. 4. Invarious embodiments a first copy of the user behavior profile 406,profile copy ‘1’ 604 is used by a first system, system ‘1’ 606, andadditional copies, profile copy ‘n’ 608, are used by additional systems‘n’ 608 to perform various user behavior monitoring operations. Incertain embodiments, additions to profile copy ‘1’ 604 of the userbehavior profile 408 results in the same additions to profile copies ‘n’608. As a result, systems ‘1’ 606 through ‘n’ 608 are kept in synchregarding the user's 602 user behavior. Accordingly, each system ‘1’ 604through ‘n’ 610 is apprised of any anomalous or malicious user behaviorenacted by the user 602, regardless of which system was being used whenthe anomalous or malicious behavior occurred.

FIGS. 7a and 7b are a generalized flowchart of the performance of userbehavior profile origination operations in accordance with an embodimentof the invention. In this embodiment, user behavior profile originationoperations are begun in step 702, followed by the selection of a targetuser in step 706 for user behavior profile origination. An unpopulateduser behavior profile is then generated for the selected user in step706, followed by the identification of known user behavior elementsassociated with the selected user in step 708.

A user behavior element associated with the user is then selected forvalidation in step 710, followed by the performance of user behaviorvalidation operations in step 712 to determine whether the selected userbehavior element is suspect. In various embodiments, the method by whichthe user behavior element is validated is a matter of design choice. Adetermination is then made in step 714 whether the user behavior elementis suspect. If so, then the user behavior element is appended as asuspect user behavior element to the user's user behavior profile instep 716. Otherwise, the user behavior element is appended to the user'suser behavior profile in step 718.

Thereafter, or once the suspect user behavior element is appended to theuser's user behavior profile in step 716, a determination is made instep 720 whether to select another user behavior element for validation.If so, the process is continued, proceeding with step 710. Otherwise,user behavior elements that have been appended to the user behaviorprofile are processed in step 722 to generate a user behavior hashvalue, described in greater detail herein. Then, in step 724, the userbehavior elements that have been appended to the user behavior profileare processed to generate a user behavior score, likewise described ingreater detail herein. The resulting user behavior hash value and scoreare then appended to the user behavior profile in step 726.

In turn, the user behavior profile is stored in step 728 for use in userbehavior monitoring operations. In one embodiment, the user behaviorprofile is stored in a repository of user behavior profiles. In anotherembodiment, the repository of user behavior profiles is implemented foruse by a single user behavior monitoring system. In yet anotherembodiment, the repository of user behavior profiles is implemented foruse by a plurality of user behavior monitoring systems. In variousembodiments, the user behavior profile is stored in a user behaviorblockchain, described in greater detail herein. A determination is thenmade in step 730 whether to end user behavior profile originationoperations. If not, the process is continued, proceeding with step 704.Otherwise, user behavior profile origination operations are ended instep 732.

FIG. 8 is a generalized flowchart of the performance of user behaviormonitoring operations implemented in accordance with an embodiment ofthe invention to detect acceptable, anomalous, and malicious userbehavior. In this embodiment, user behavior monitoring operations arebegun in step 802, followed by the performance of user authenticationoperations, familiar to those of skill in the art, in step 804. Then, instep 806, the user's user behavior profile is retrieved, followed by theongoing monitoring of the user's user behavior activities in step 808.The user's user behavior activities are processed in step 810 todetermine their associated user behavior element, which is then comparedto the user's user behavior profile in step 812.

A determination is then made in step 814 whether the user's current userbehavior element is acceptable. If so, then the user behavior element ismarked as acceptable in block 816. Otherwise, a determination is made instep 818 whether the user's current user behavior element is anomalous.If so, then the current user behavior element is marked as anomalous instep 820, followed by the performance of anomalous user behavioroperations in step 822. In one embodiment, the anomalous user behavioris stored for later review. In another embodiment, a securityadministrator is notified of the anomalous user behavior. However, if itwas determined in step 818 that the current user behavior element is notanomalous, then the current user behavior element is marked as maliciousin step 824, followed by the performance of malicious user behavioroperations in step 826. Thereafter, or once the current user behaviorelement has been marked as acceptable or anomalous in steps 816 or 820,the current user behavior element is appended to the user's userbehavior profile in step 828.

A determination is then made in step 830 whether to end user behaviormonitoring operations. If not, then the process continues, proceedingwith step 808. Otherwise, user behavior profile scoring operations,described in greater detail herein, are performed in step 832 togenerate a user behavior score. User behavior hashing operations,likewise described in greater detail herein, are then performed in step834 to generate a user behavior hash values. The resulting cyberbehavior score and hash value are then appended to the user's userbehavior profile in step 836. User behavior monitoring operations arethen ended in step 838.

Although the present invention has been described in detail, it shouldbe understood that various changes, substitutions and alterations can bemade hereto without departing from the spirit and scope of the inventionas defined by the appended claims.

1. A computer-implementable method for generating a cyber behaviorprofile, comprising: monitoring electronically-observable user behavior;converting the electronically-observable user behavior into electronicinformation representing the electronically-observable user behavior,the electronic information representing the electronically-observableuser behavior comprising respective user behavior elements; generating auser behavior profile based upon the electronic information representingthe electronically-observable user behavior; storing informationrelating to the user behavior profile in a behavior blockchain;determining whether a user behavior is suspect generating a userbehavior block representing the suspect user behavior; and, appendingthe user behavior block to the behavior blockchain, the user behaviorblock comprising a known good user behavior representation when the userbehavior is not suspect and a suspect user behavior representation whenthe user behavior is suspect.
 2. The method of claim 1, wherein: theelectronic information representing the user interactions comprise auser behavior element; and further comprising storing informationrelating to the user behavior element in a user behavior block of thebehavior blockchain.
 3. The method of claim 1, wherein: the userbehavior profile is based upon at least one of an identification factorand a user behavior factor.
 4. The method of claim 2, wherein: the userbehavior block comprises a transaction payload; and, the transactionpayload includes a representation of the user behavior profile.
 5. Themethod of claim 4, wherein: the transaction payload comprises executablecode, the executable code being used by a user behavior monitoringsystem to detect at least one of acceptable behavior, anomalousbehavior, malicious behavior and unknown behavior being enacted by auser.
 6. The method of claim 4, wherein: the transaction payloadcomprises a user behavior score, the user behavior score being used by auser behavior monitoring system to assess a particular user whileenacting a given user behavior.
 7. A system comprising: a processor; adata bus coupled to the processor; and a non-transitory,computer-readable storage medium embodying computer program code, thenon-transitory, computer-readable storage medium being coupled to thedata bus, the computer program code interacting with a plurality ofcomputer operations and comprising instructions executable by theprocessor and configured for: monitoring electronically-observable userbehavior; converting the electronically-observable user behavior intoelectronic information representing the electronically-observable userbehavior, the electronic information representing theelectronically-observable user behavior comprising respective userbehavior elements; generating a user behavior profile based upon theelectronic information representing the electronically-observable userbehavior; storing information relating to the user behavior profile in abehavior blockchain; determining whether a user behavior is suspectgenerating a user behavior block representing the suspect user behavior;and, appending the user behavior block to the behavior blockchain, theuser behavior block comprising a known good user behavior representationwhen the user behavior is not suspect and a suspect user behaviorrepresentation when the user behavior is suspect.
 8. The system of claim7, wherein: the electronic information representing the userinteractions comprise a user behavior element; and the instructions arefurther configured for: storing information relating to the userbehavior element in a user behavior block of the behavior blockchain. 9.The system of claim 8, wherein: the user behavior profile is based uponat least one of an identification factor and a user behavior factor. 10.The system of claim 8, wherein: the user behavior block comprises atransaction payload; and, the transaction payload includes arepresentation of the unique cyber behavior profile.
 11. The system ofclaim 10, wherein: the transaction payload comprises executable code,the executable code being used by a user behavior monitoring system todetect at least one of acceptable behavior, anomalous behavior,malicious behavior and unknown behavior being enacted by a user.
 12. Thesystem of claim 10, wherein: the transaction payload comprises a userbehavior score, the user behavior score being used by a user behaviormonitoring system to assess a particular user while enacting a givenuser behavior.
 13. A non-transitory, computer-readable storage mediumembodying computer program code, the computer program code comprisingcomputer executable instructions configured for: monitoringelectronically-observable user behavior; converting theelectronically-observable user behavior into electronic informationrepresenting the electronically-observable user behavior, the electronicinformation representing the electronically-observable user behaviorcomprising respective user behavior elements; generating a user behaviorprofile based upon the electronic information representing theelectronically-observable user behavior; storing information relating tothe user behavior profile in a behavior blockchain; determining whethera user behavior is suspect generating a user behavior block representingthe suspect user behavior; and, appending the user behavior block to thebehavior blockchain, the user behavior block comprising a known gooduser behavior representation when the user behavior is not suspect and asuspect user behavior representation when the user behavior is suspect.14. The non-transitory, computer-readable storage medium of claim 13,wherein: the electronic information representing the user interactionscomprise a user behavior element; and the instructions are furtherconfigured for: storing information relating to the user behaviorelement in a user behavior block of the behavior blockchain.
 15. Thenon-transitory, computer-readable storage medium of claim 14, wherein:the user behavior profile is based upon at least one of anidentification factor and a user behavior factor.
 16. Thenon-transitory, computer-readable storage medium of claim 14, wherein:the user behavior block comprises a transaction payload; and, thetransaction payload includes a representation of the unique cyberbehavior profile.
 17. The non-transitory, computer-readable storagemedium of claim 16, wherein: the transaction payload comprisesexecutable code, the executable code being used by a user behaviormonitoring system to detect at least one of acceptable behavior,anomalous behavior, malicious behavior and unknown behavior beingenacted by a user.
 18. The non-transitory, computer-readable storagemedium of claim 16, wherein: the transaction payload comprises a userbehavior score, the user behavior score being used by a user behaviormonitoring system to assess a particular user while enacting a givenuser behavior.
 19. The non-transitory, computer-readable storage mediumof claim 13, wherein the computer executable instructions are deployableto a client system from a server system at a remote location.
 20. Thenon-transitory, computer-readable storage medium of claim 13, whereinthe computer executable instructions are provided by a service providerto a user on an on-demand basis.